ADAPTIVE POLLING IN SOFTWARE-DEFINED NETWORKING (SDN) ENVIRONMENTS
Granted: April 9, 2020
Application Number:
20200112500
Example methods are provided for a network device to perform adaptive polling in a software-defined networking (SDN) environment. One example method may comprise: operating in a polling mode at a current polling round to detect zero or more packets that require packet processing by the network device. The method may also comprise: determining packet characteristic information associated with multiple polling rounds that include the current polling round and one or more previous polling…
NEAR ZERO DOWNTIME APPLICATION UPGRADE
Granted: March 26, 2020
Application Number:
20200097280
A system for upgrading an application running on a virtual computing instance (VCI) can include a processing resource, a memory resource, and a VCI manager. The VCI manager can be executed by the processing resource and the memory resource and can be configured to cause a first VCI that is running the application to be copied as a second VCI, cause an updated version of the application to be installed on the second VCI, and cause a private network to be generated between the first VCI…
Remote Access Over Internet Using Reverse Session-Origination (RSO) Tunnel
Granted: March 19, 2020
Application Number:
20200092156
A remote user sends a user request to a relay server that, in turn, forwards the user request (modified or unmodified) through a reverse session-origination (RSO) tunnel to an on-premises network client. In other words, while the user requests flow from outside the client network to the client network, the requests of the delivery protocol for the tunnel flow in the reverse direction, i.e., from the client network toward the relay server and/or the remote user. A server agent, executing…
RUNTIME INFORMATION TRANSFER BETWEEN KERNEL MODULES
Granted: March 12, 2020
Application Number:
20200081638
Example methods and systems are provided for a computer system to transfer runtime information between a first kernel module and a second kernel module. In one example, the method may comprise assigning ownership of a memory pool to the first kernel module; and the first kernel module accessing the memory pool to store runtime information associated with one or more operations performed by the first kernel module. The method may also comprise releasing ownership of the memory pool from…
MANAGING AN UPGRADE OF A VIRTUALIZATION INFRASTRUCTURE COMPONENT
Granted: March 5, 2020
Application Number:
20200073648
In a method for managing an upgrade of a virtualization infrastructure component, a plurality of metadata manifests corresponding to a plurality of software upgrade bundles is received, a software upgrade bundle for upgrading a virtualization infrastructure component from a source version to a target version, a metadata manifest comprising a listing of applications comprised within a corresponding software upgrade bundle and installation instructions for the applications comprised within…
AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER THAT USES LOCAL AGENTS
Granted: February 27, 2020
Application Number:
20200065702
The current document is directed to automated reinforcement-learning-based application managers that use local agents. Local agents provide finer-granularity monitoring of an application or application subcomponents and provide continued application management in the event of interruption of network traffic between an automated reinforcement-learning-based application manager and the application or application subcomponents managed by the automated reinforcement-learning-based…
SENDER SIDE ASSISTED FLOW CLASSIFICATION
Granted: February 27, 2020
Application Number:
20200067842
A method for a sender side assisted flow classification is disclosed. In an embodiment, a method comprises detecting a packet by a network virtualization layer engine implemented in a hypervisor on a sender side of a virtualization computer system; and determining, by the network virtualization layer engine, whether the packet requires special processing. In response to determining that the packet requires special processing, a special processing flag is inserted in a certain field of an…
FIRST HOP ROUTER IDENTIFICATION IN DISTRIBUTED VIRTUALIZED NETWORKS
Granted: February 27, 2020
Application Number:
20200067819
A method for identifying a first hop router (“FHR”) in a distributed virtualized network is presented. In an embodiment, a method comprises receiving a multicast message on an incoming interface. In response to receiving the multicast message, the router determines whether the router is a FHR for the multicast message, i.e., whether, in response to generating and transmitting a hello multicast message, the router does not receive a response on the incoming interface; or whether an…
SIMULATOR-TRAINING FOR AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION-MANAGERS
Granted: February 27, 2020
Application Number:
20200065704
The current document is directed to methods and systems for simulation-based training of automated reinforcement-learning-based application managers. Simulators are generated from data collected from controlled computing environments controlled and may employ any of a variety of different machine-learning models to learn state-transition and reward models. The current disclosed methods and systems provide facilities for visualizing aspects of the models learned by a simulator and for…
ADVERSARIAL AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION-MANAGER TRAINING
Granted: February 27, 2020
Application Number:
20200065703
The current document is directed to automated reinforcement-learning-based application managers that that are trained using adversarial training. During adversarial training, potentially disadvantageous next actions are selected for issuance by an automated reinforcement-learning-based application manager at a lower frequency than selection of next actions, according to a policy that is learned to provide optimal or near-optimal control over a computing environment that includes one or…
ADMINISTRATOR-MONITORED REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER
Granted: February 27, 2020
Application Number:
20200065118
The current document is directed to an administrator-monitored reinforcement-learning-based application manager that can be deployed in various different computational environments to manage the computational environments with respect to one or more reward-specified goals. Certain control actions undertaken by the administrator-monitored reinforcement-learning-based application manager are first proposed, to one or more administrators or other users, who can accept or reject the proposed…
AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER THAT USES ACTION TAGS AND METRIC TAGS
Granted: February 27, 2020
Application Number:
20200065701
The current document is directed to an automated reinforcement-learning-based application manager that uses action tags and metric tags. In various implementations, actions and metrics are associated with tags. Different types of tags can contain different types of information that can be used to greatly improve the computational efficiency by which the reinforcement-learning-based application manager explores the action-state space in order to determine and maintain an optimal or…
TRANSFERABLE TRAINING FOR AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION-MANAGERS
Granted: February 27, 2020
Application Number:
20200065670
The current document is directed to transfer of training received by a first automated reinforcement-learning-based application manager while controlling a first application is transferred to a second automated reinforcement-learning-based application manager which controls a second application different from the first application. Transferable training provides a basis for automated generation of applications from application components. Transferable training is obtained from…
SAFE-OPERATION-CONSTRAINED REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER
Granted: February 27, 2020
Application Number:
20200065495
The current document is directed to a safe-operation-constrained reinforcement-learning-based application manager that can be deployed in various different computational environments, without extensive manual modification and interface development, to manage the computational environments with respect to one or more reward-specified goals. Control actions undertaken by the safe-operation-constrained reinforcement-learning-based application manager are constrained, by stored action…
HANDLING OF AN INDEX UPDATE OF TIME SERIES DATA
Granted: February 27, 2020
Application Number:
20200065411
In a computer-implemented method for handling of an index update, time series data is received at an ingestion node of a time series data monitoring system. An index update is determined based on the time series data. The index update is stored to an index database of the time series data monitoring system. The index update is forward to a plurality of query nodes of the time series data monitoring system.
HANDLING TIME SERIES INDEX UPDATES AT INGESTION
Granted: February 27, 2020
Application Number:
20200065407
In a computer-implemented method for proactive handling of an index update, a data point is received at an ingestion node of a time series data monitoring system. It is determined whether an update to a local index of the ingestion node is necessitated based on the data point and the local index. Provided the update to the local index is necessitated, an index entry corresponding to the data point in the local index is updated based on the data point. The index entry corresponding to the…
PROCESSES AND SYSTEMS FOR FORECASTING METRIC DATA AND ANOMALY DETECTION IN A DISTRIBUTED COMPUTING SYSTEM
Granted: February 27, 2020
Application Number:
20200065213
Computational processes and systems are directed to forecasting time series data and detection of anomalous behaving resources of a distributed computing system data. Processes and systems comprise off-line and on-line modes that accelerate the forecasting process and identification of anomalous behaving resources. In the off-line mode, recurrent neural network (“RNN”) is continuously trained using time series data associated with various resources of the distributed computing…
AUTOMATED REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER THAT LEARNS AND IMPROVES A REWARD FUNCTION
Granted: February 27, 2020
Application Number:
20200065157
The current document is directed to automated reinforcement-learning-based application managers that learn and improve the reward function that steers reinforcement-learning-based systems towards optimal or near-optimal policies. Initially, when the automated reinforcement-learning-based application manager is first installed and launched, the automated reinforcement-learning-based application manager may rely on human-application-manager action inputs and resulting state/action…
COMPUTATIONALLY EFFICIENT REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER
Granted: February 27, 2020
Application Number:
20200065156
The current document is directed to automated reinforcement-learning-based application managers that obtain increased computational efficiency by reusing learned models and by using human-management experience to truncate state and observation vectors. Learned models of managed environments that receive component-associated inputs can be partially or completely reused for similar environments. Human managers and administrators generally use only a subset of the available metrics in…
MODULAR REINFORCEMENT-LEARNING-BASED APPLICATION MANAGER
Granted: February 27, 2020
Application Number:
20200065128
The current document is directed to a modular reinforcement-learning-based application manager that can be deployed in various different computational environments without extensive modification and interface development. The currently disclosed modular reinforcement-learning-based application manager interfaces to observation and action adapters and metadata that provide a uniform and, in certain implementations, self-describing external interface to the various different computational…
